MonkerSolver Troubleshooting Guide — Common Errors and Fixes

MonkerSolver is powerful but it can throw up some frustrating errors, especially when you are first getting started or pushing your hardware to its limits. This guide covers the most common problems and how to fix them.

1. Out of Memory Error

This is the most common error serious MonkerSolver users will hit. You are mid-solve and MonkerSolver stops with a message along the lines of:

This happens because MonkerSolver has run out of RAM. PLO trees are enormous compared to NL — the number of possible hand combinations means that large trees with multiple bet sizes and raises across multiple streets can consume hundreds of gigabytes of RAM.

How to fix it

• Reduce your bet sizes — the more bet sizes you include per node, the exponentially larger the tree becomes. Cut down to one or two sizes per street and see if the solve completes.
• Reduce raise options — having multiple raise sizes multiplies the tree size dramatically. Start with a single raise size and add more once you have more RAM.
• Increase your volatility target — a lower accuracy target means MonkerSolver stops sooner and uses less memory to get there.
• Get more RAM — ultimately the permanent fix is more RAM. For serious PLO solving I run a 512GB server and it means I rarely think about memory limits. See the server guide for more details.

2. How to Speed Up MonkerSolver Solves

Solves feeling slow? There are several things you can do to get results faster.

Set the correct thread count

MonkerSolver defaults to 16 threads regardless of how many CPU cores your machine has. If you have more than 16 cores you are leaving performance on the table. Go to Settings → General → Threads and set it to match your actual core count. You can also adjust it live in the Solve tab using the + and - buttons.

Reduce bet and raise sizes

The size of the tree — and therefore how long it takes to solve — grows exponentially with the number of bet and raise sizes you include. Each additional bet size roughly doubles the tree. If you are running full streets with 3 bet sizes and 2 raise sizes, cutting to 2 bet sizes and 1 raise size will reduce solve time dramatically without sacrificing much strategic insight for most study purposes.

Use a higher volatility target

MonkerSolver solves to a volatility (accuracy) target. A lower number means higher accuracy but longer solve times. For initial exploration of a spot, solving to 3 or 4 volatility is perfectly fine and much faster. Save lower volatility solves for spots you want to study in depth.

Get better hardware

More CPU cores means faster solves — it really is that simple. My current server runs dual Intel Xeon E5-2695v4 processors giving 36 cores and 72 threads, and a SRP 100bb solve to 2 volatility with 1-2 bet sizes takes around 3 hours. On a typical home PC the same solve could take days. If you are serious about volume solving, a dedicated server is the right investment.

3. MonkerSolver Won't Open

If MonkerSolver fails to launch, work through these fixes in order:

• Check Java is installed — MonkerSolver runs on Java. If Java is missing or outdated it won't open. Download the latest Java Runtime Environment from java.com and try again.
• Check you have enough free RAM — MonkerSolver needs available RAM to launch. Close other applications and try again.
• Check the MonkerSolver.l4j.ini file — this file (in your MonkerSolver folder) controls how much RAM is allocated to the program on startup. If it is set to more RAM than your machine has available, MonkerSolver will fail to open. Open the file in Notepad and reduce the Xmx value.
• Run as administrator — on Windows, right-click the MonkerSolver launcher and select Run as Administrator.
• Reinstall — if nothing else works, a clean reinstall usually fixes launch issues.

4. MonkerSolver Crashes Mid-Solve

A crash mid-solve is almost always a memory issue — the tree has grown larger than available RAM during the solve process. The fixes are the same as the out of memory error above: reduce bet sizes, raise options, or get more RAM.

One other cause worth checking is Windows page file settings. If your page file (virtual memory) is set too small, Windows can crash applications when physical RAM runs out. Set your page file to at least 1.5x your physical RAM as a safety net.

5. VNC Connection Issues (Linux Server)

If you are running MonkerSolver on a Linux server via VNC and can't connect or see a blank screen, the most common causes are:

• Blank grey screen — install dbus-x11, kill the VNC server and restart it. This is the most common issue on Ubuntu 22.04+.
• Too many authentication failures — bots are hitting your VNC port. Restrict access using your firewall to your home IP only.
• VNC session ended — if you killed the VNC session rather than just closing the viewer window, any running sims will have stopped. Always close the viewer window rather than terminating the session.

For the full Linux setup guide including all the errors we hit and how to fix them, see our MonkerSolver Linux Guide.

6. MonkerSolver Running Slow on a Home PC

If you are running MonkerSolver on a regular home PC or laptop, there is a limit to how much you can improve performance through settings alone. The root cause is usually insufficient RAM and too few CPU cores. Practical options:

• Upgrade your PC's RAM if possible — going from 32GB to 64GB makes a noticeable difference.
• Close all other applications while solving to free up RAM and CPU.
• Use MonkerSolver's queue overnight — set your sims running before bed and check them in the morning rather than waiting around for each one to finish.
• Consider a dedicated server if you are doing regular serious study — the monthly cost quickly pays for itself in time saved.

If you have any questions about MonkerSolver that aren't covered here, feel free to reach out at support@plodalong.com and we'll do our best to help.